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Try executing this chunk by clicking the Run button within the chunk or by placing your cursor inside it and pressing Ctrl+Shift+Enter. # Cellchat

source("./tianfengRwrappers.R")

library(CellChat)

ds2 <- readRDS("ds2.rds")
CA_dataset2 <- readRDS("CA_dataset2.rds")
# saveRDS(CA_dataset2,"CA_dataset2.rds")
umapplot(CA_dataset2)

Warning: Using `as.character()` on a quosure is deprecated as of rlang 0.3.0.
Please use `as_label()` or `as_name()` instead.
This warning is displayed once per session.

f("DLX5",EC_SMC)
umapplot(EC_SMC)

saveRDS(EC_SMC,"EC_SMC.rds")

CellChat

配体-受体+辅因子

computeAveExpr(cor, features = c("BMP2","BMP4","BMP6","BMPR1B","BMPR1A","BMPR2","ACVR2A"), type =  "truncatedMean", trim = 0.05)

                3        EC0         EC1         EC2 Fibroblast Fibromyocyte    Pericyte        SMC1       SMC2
BMP2   0.03150669 0.02623810 0.003702709 0.202131802 0.00000000   0.00000000 0.028212306 0.000000000 0.00000000
BMP4   0.00000000 0.02969807 0.064427142 0.535072542 0.14289603   0.05976591 0.000000000 0.008078115 0.02235959
BMP6   0.33885091 0.00000000 0.000000000 0.430656995 0.00000000   0.00000000 0.000000000 0.000000000 0.00000000
BMPR1B 0.00000000 0.00000000 0.000000000 0.000000000 0.08194540   0.00000000 0.000000000 0.008751292 0.07602259
BMPR1A 0.00000000 0.00000000 0.000000000 0.006539124 0.05175499   0.03366126 0.009241962 0.057668768 0.02832214
BMPR2  0.30466733 0.28211628 0.328085107 0.880202371 0.11521646   0.13015395 0.078799890 0.157702091 0.11248721
ACVR2A 0.00000000 0.00000000 0.000000000 0.000000000 0.01848392   0.00000000 0.000000000 0.000000000 0.00000000

write.csv(df.net,"./datatable/EC_SMC_cellchat_res.csv", row.names = F)

cellchat可视化

cor <- readRDS("EC_SMC_cellchat.rds")

# cor@idents <- plyr::revalue(cor@idents, c("Mod_SMC"="Fibroblast", "SMC_0"="SMC1","SMC_1"="Fibromyocyte",
#                    "SMC_2"="Pericyte","SMC_3"="SMC2"))

table(cor@idents)
groupSize <- as.numeric(table(cor@idents))
netVisual_circle(cor@net$weight, vertex.weight = groupSize, weight.scale = T, label.edge= F, title.name = "Interaction weights/strength")
netVisual_heatmap(cor, measure = "weight", signaling = NULL, color.heatmap = c("#f1f1f1", "#ff2121"))

#一次分析不同细胞亚群
mat <- cor@net$weight
for (i in 1:nrow(mat)) {
  mat2 <- matrix(0, nrow = nrow(mat), ncol = ncol(mat), dimnames = dimnames(mat))
  mat2[i, ] <- mat[i, ]
  netVisual_circle(mat2, vertex.weight = groupSize, weight.scale = T, edge.weight.max = max(mat), title.name = rownames(mat)[i])
}

# pheatmap(mat, display_numbers = FALSE, number_color ="black", cluster_rows = FALSE, 
         # cluster_cols = FALSE, color = colorRampPalette(c("#1E90FF", "white", "#ff2121"))(400), border_color = NA)

netVisual_aggregate(cor, signaling = pathways.show, layout = "circle")

netVisual_bubble(cor, sources.use = 4, targets.use = c(5:9), pairLR.use = LR_show, remove.isolate = F) #EC2 target

Comparing communications on a single object 

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